In this paper, we present an unsupervised hybrid model which combines statistical, lexical, linguistic, contextual, and temporal features in a generic EMbased framework to harvest...
In this paper, we adapt a statistical learning approach, inspired by automated topic segmentation techniques in speech-recognized documents to the challenging protein segmentation ...
Betty Yee Man Cheng, Jaime G. Carbonell, Judith Kl...
We present an implemented model for speech recognition in natural environments which relies on contextual information about salient entities to prime utterance recognition. The hyp...
Progressive sequence model refinement by means of iterative searches is an effective technique for high sensitivity database searches and is currently employed in popular tools s...
Control systems must increasingly be designed to involve collections of hardware and software components, both of which may evolve over the lifetime of the system, and which are e...
Simon Dobson, Eoin Bailey, Stephen Knox, Ross Shan...